Regulwar Ganesh (10 results)
- Softcover
Seller: preigu, Osnabrück, Germanypreigu
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Taschenbuch. Condition: Neu. Extraction of Texture Features by Euclidean, Canberra & Both Distance | For Content Based Image Retrieval | Ganesh Bhaiyya Regulwar (u. a.) | Taschenbuch | 104 S. | Englisch | 2012 | LAP LAMBERT Academic Publishing | EAN 9783843357401 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengeri…cher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
- Softcover
Seller: Mispah books, Redhill, SURRE, United KingdomMispah books
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Paperback. Condition: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
- Softcover
Seller: Ria Christie Collections, Uxbridge, United KingdomRia Christie Collections
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- Softcover
Seller: PBShop.store UK, Fairford, GLOS, United KingdomPBShop.store UK
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PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.
- Softcover
Seller: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
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Language: English
Published by LAP LAMBERT Academic Publishing Sep 2012, 2012
- Softcover
- Print on Demand
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Texture describes the content of many real world images: for example, clouds, trees, bricks, hair, fabric etc. all of which have textural characteristics.Feature extraction is one of the most important tasks for efficient and accura…te image retrieval purpose. In this book we are going to use Cosine-modulated wavelet transform based technique for extraction of texture features. The major advantages of Cosine-modulated wavelet transform are less implementation complexity, good filter quality, and ease in imposing the regularity conditions. Texture features are obtained by computing the energy, standard deviation and their combination on each subband of the decomposed image. To check the retrieval performance, texture database of 1856 textures is created from Brodatz album. Retrieval efficiency and accuracy using Cosine-modulated wavelet based features will be found to be superior to other existing methods. 104 pp. Englisch.
- Softcover
- Print on Demand
Seller: moluna, Greven, Germanymoluna
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Regulwar Ganesh BhaiyyaMaster of Engineering in Information Technology.He is Working as an Assistant Professor in Engineering & Technology Institute at Maharashtra,INDIA.Area of research interest includ…es image processing,Software E.
Language: English
Published by LAP LAMBERT Academic Publishing Sep 2012, 2012
- Softcover
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Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Texture describes the content of many real world images: for example, clouds, trees, bricks, hair, fabric etc. all of which have textural characteristics.Feature extraction is one of the most important tasks for efficient and accurate i…mage retrieval purpose. In this book we are going to use Cosine-modulated wavelet transform based technique for extraction of texture features. The major advantages of Cosine-modulated wavelet transform are less implementation complexity, good filter quality, and ease in imposing the regularity conditions. Texture features are obtained by computing the energy, standard deviation and their combination on each subband of the decomposed image. To check the retrieval performance, texture database of 1856 textures is created from Brodatz album. Retrieval efficiency and accuracy using Cosine-modulated wavelet based features will be found to be superior to other existing methods.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 104 pp. Englisch.
- Softcover
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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Texture describes the content of many real world images: for example, clouds, trees, bricks, hair, fabric etc. all of which have textural characteristics.Feature extraction is one of the most important tasks for efficient and accurate im…age retrieval purpose. In this book we are going to use Cosine-modulated wavelet transform based technique for extraction of texture features. The major advantages of Cosine-modulated wavelet transform are less implementation complexity, good filter quality, and ease in imposing the regularity conditions. Texture features are obtained by computing the energy, standard deviation and their combination on each subband of the decomposed image. To check the retrieval performance, texture database of 1856 textures is created from Brodatz album. Retrieval efficiency and accuracy using Cosine-modulated wavelet based features will be found to be superior to other existing methods.
- Softcover
- Print on Demand
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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£ 410.16
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Today, data fuels everything we do in a highly connected world. However, traditional environmental monitoring methods often fail to provide timely and accurate data for effective decision-making in today's rapidly changing ecosystems. Th…e reliance on manual data collection and outdated technologies results in gaps in data coverage, making it challenging to detect and respond to environmental changes in real time. Additionally, integration between monitoring systems and advanced data analysis tools is necessary to derive actionable insights from collected data. As a result, environmental managers and policymakers face significant challenges in effectively monitoring, managing, and conserving natural resources in a rapidly evolving environment. Machine Learning for Environmental Monitoring in Wireless Sensor Networks offers a comprehensive solution to the limitations of traditional environmental monitoring methods. By harnessing the power of Wireless Sensor Networks (WSNs) and advanced machine learning algorithms, this book presents a novel approach to ecological monitoring that enables real-time, high-resolution data collection and analysis. By integrating WSNs and machine learning, environmental stakeholders can gain deeper insights into complex ecological processes, allowing for more informed decision-making and proactive management of natural resources.
